THE TURKISH ONLINE JOURNAL OF EDUCATIONAL TECHNOLOGY JULY 2005 Volume 4 - Issue 3 Assoc. Prof. Dr. Aytekin İşman Editor-in-Chief Prof. Dr. Jerry Willis Editor Fahme Dabaj Associate Editor ISSN: 1303-6521
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 TOJET Volume 4 Issue 3 July 2005 Table of Contents A Computer Assessment Tool for Concept Mapping Recai AKKAYA, Erol KARAKIRIK, Soner DURMUŞ A Computer Based Problem Solving Environment in Chemistry İbrahim BILGIN, Erol KARAKIRIK A Metadata Model for E-Learning Coordination through Semantic Web Languages Atila ELÇİ A Model for Integrating New Technologies into Pre-Service Teacher Training Programs Ajman University (A Case Study) Ali Zuhdi H. SHAQOUR A Multidisciplinary Education Frameworks that Exploits IT Undergraduates to Eliminating Lack of IT Skills in Non-IT Graduate Disciplines Alev ELÇİ, Hasan AMCA A New Model for the World of Instructional Design: A New Model Aytekin İŞMAN, Mehmet ÇAĞLAR, Fahme DABAJ, Hatice ERSÖZLÜ A Study about Students Misconceptions in Force and Motion Concepts by Incorporating a Webassisted Physics Program Neşet DEMİRCİ Computers: Educational Technology Paradox? Hajah Rugayah Hj. HASHIM, Wan Narita MUSTAPHA Costs & Benefits of Guided Discovery Architecture Online Programs M. Tuncay SARITAŞ Implementing Project Based Learning in Computer Classroom Aşkın ASAN, Zeynep HALİLOĞLU Mathematics Teachers Attitudes toward the Computers Mehmet A. OCAK Anadolu Üniversitesi Açıköğretim Fakültesi Sisteminde Soru Yazarlarının Soru Hazırlamada karşılaştıkları güçlükler. Nejdet KARADAĞ Basit Bir Mikroişlemci Yapısının Web Tabanlı Çoklu Ortam ile Öğretimi. Atakan KÖREZ, A. Yılmaz ÇAMURCU Bilgi Teknolojilerinin Öğrenim Alanı Planlamasına Etkileri: İlköğretim Okullarının Derslik ve Kütüphane Mekanları Örneğinde Mehtap ÖZBAYRAKTAR Bilgi ve İletişim Teknolojilerinin Öğrenme-Öğretme Sürecine Entegrasyonunda Öğretmenlerin Durumu Yasemin DEMİRASLAN, Yasemin KOÇAK USLUEL Bilginin Eğitim Teknolojilerinden Yararlanarak Eğitimde Paylaşımı.. Bahadtin RÜZGAR Bilgisayar Destekli Fizik Öğretiminde Çalışma Yapraklarına Dayalı Materyal Geliştirme ve Uygulama Ahmet Zeki SAKA, Metin YILMAZ Dijital Hikaye Anlatımının Bileşenleri Ayşenur İNCEELLİ İşitme Engelli Çocuklarda Bireyselleştirilmiş Okuma Eğitimi Ümit GİRGİN Sanal Gerçeklik ve Eğitim Amaçlı Kullanılması Yücel KAYABAŞI Sosyal Bilgiler Dersinde Gazete Kullanımı Handan DEVECİ 3 7 12 18 25 33 40 49 54 68 82 89 96 101 109 114 120 132 143 151 159 Copyright The Turkish Online Journal of Educational Technology 2002 2
A COMPUTER ASSESSMENT TOOL FOR CONCEPT MAPPING Recai Akkaya, Erol Karakırık, Soner Durmuş Abant Izzet Baysal University, Faculty of Education ABSTRACT Current educational theories emphasize assessment as a vital part of teaching-learning process. Alternative assessment techniques aim to expose and promote the process of the learning rather than the final outcome. Concept mapping is a technique for representing conceptual knowledge and relationships between concepts in a graphical form. Requiring to construct concept maps encourages learners to organize concepts and the relationships between them in a hierarchical structure. Although constructing concept maps might be difficult in every domain including mathematics and might require extensive domain knowledge, it is essential to employ concept mapping technique in order to reveal learner s conceptual understanding. Hence, asking learners construct their concept maps or to fill missing parts in a pre-designed concept maps might be used as a part of the assessment process. A prototype computer system, called Concept Map Assessor (CMA), is designed to help learners to construct concept maps and to evaluate their performances in pre-designed concept maps. In this study, the basic features and elements of the CMA will be presented and its possible contributions to mathematics education will be discussed. INTRODUCTION Assessment is essential part of teaching-learning process. It gives the picture of what students gained and problems they had. Classical assessment techniques such as multiple choice, true-false type tests, etc. emphasize the product not the process. Alternative assessment techniques have developed to assess the process not the product (Anderson, 1988; Nowak & Gowin, 1984). Concept mapping technique can be viewed as an example of alternative assessment techniques. This paper will explain how to use and assess this technique in mathematics domain, give information about computerized version of concept mapping technique called Computerized Concept Map (CCM) and a few examples with computer screen shots will be provided. CONCEPT MAPPING IN MATH The idea of letting students to construct concept maps was developed by Novak and Gowing (1984). This technique was supported on the studies of different mathematics educators (Skemp, 1987; Park & Trave, 1996; Lanier, 1997). The process of making concept maps helps students understand connections between different ideas. Mathematics requires abstractions based on concrete, semi-concrete or abstract experiences of students. Organization of mathematical ideas or relations is vital and most students have problems on developing relational understanding. Engaging in meaningful learning requires relevant prior knowledge, meaningful material and the choice of the learner (Novak, 1998). Concept maps enables students to relate newly learned ideas. It also helps students connect new ones with old ones (Mwakapanda & Adler, 2002, p. 62). The idea of concept mapping can be rooted back to the studies of Piaget and Ausebel. New piece of information causes the disequilibrium with old ones, then student reach to cognitive equilibrium by assimilation or accommodation. Reaching to cognitive equilibrium means that students formed the new cognitive/conceptual schema (Hamachek, 1986). Concept maps is a mean to force students to organize their conceptual schema and present it in a peculiar way (Roth & Roychoudhury, 1992, p. 357). This representation gives teacher chance to assess their and students learning. Misconceptions can be revealed by asking students to construct concept map. Concept maps are dynamic and students add new components based on their experiences. Since mathematics consists of complicated and complex forms of relations, as students gain more insight, they develop complicated and integrated concept maps. Concept maps were constructed mostly at the end of a lesson and/or subject. This way, students reorganize their ideas and make connections between the smaller points within the subject. For example, one could construct concept maps about quadrilaterals. By the help of a concept map, one could visualize the certain relations under a specific condition among different quadrilaterals such as trapezoid, parallelogram, rectangle, rhombus and square (See Figure 1). Copyright The Turkish Online Journal of Educational Technology 2002 3
Figure 1. An example of a paper-and-pencil concept map about quadrilaterals. COMPUTERIZED CONCEPT MAPS There are many software packages for constructing concept maps such as MindGenius for Education, Mind Mapper, Inspiration, Decision Explorer, Activity Map, Kidspiration, MindGenius, Mind Manager and StarThink (The Concept Mapping Homepage, 2004). Concept maps provide a new method for organizing and browsing through information and may be an effective navigational tool for hypermedia environments (Cañas, Ford and Coffey, 1994; Ford, Cañas and Coffey, 1993). The concept map tools (CmapTools) stretch the usage of concept maps beyond knowledge representation and might serve as the browsing interface to a specified domain (Cmap Tools, 2004). There are two different approaches for designing concept mapping software: structured and unstructured. Structured approach requires users to construct concept maps in a pre-specified format such as a flow diagram or a cyclical cycle while an unstructured approach gives users freedom to choose their own format. Inspiration, Kidspiration use unstructured approach while MindGenius, Mind Manager and StarThink use a structured approach. Concept maps might show variances with respect to the individual interpretations in terms of both being general or specific and its coverage. Hence, it is very unlikely that two students produce the identical concept maps for the same task. Since students concept maps might not include the central ideas of a domain, it is difficult for teachers to grade them in a standard way. While unstructured approach is suitable for designing novel concept maps, structured approach might be more appropriate for assessing students conceptual structures because of the students difficulty of constructing concept maps from scratch. ASSESSMENT WITH CONCEPT MAPS Assessment is one of the most important parts of educational process that directs teaching, learning as well as curriculum development. Alternative assessment techniques are very important because of their focus on conceptual and meaningful understanding and process of learning not the product. Concept map as an alternative assessment technique might also enable to externalize students conceptual understanding and possible misconceptions. Concept maps might give the teacher a clear picture of students understanding by forcing students to connect and relate ideas within the subject at hand. The aim of this approach is not to pick up a certain concept of the students but to reveal their relational understanding. Utilization of the scoring rubric is useful when evaluating the students concept maps. Scoring rubrics give an overview as to what the teachers are looking for in the constructed concept maps. It is very important to have clear definitions about what to look for. It is suggested for a concept map to have a range of 3 to 6 sub-ideas from its main idea since it might require the students to clarify their most important main ideas. It is proposed that, similar to the distinction between structured and unstructured approach, assessment of concept maps might be done in two different ways. In an unstructured concept map assessment, students may construct flexible concept maps by choosing their own concept and connections. There is a proposed grading mechanism for this approach developed by Novak and Gowin (1984) based on the proximity of the sub-ideas to the main idea and the connections within the same level. In a structured concept map assessment, students may only fill the empty places in a pre-designed concept map with the given concept and relations. There is no grading mechanism that could be applied to this approach. Copyright The Turkish Online Journal of Educational Technology 2002 4
CONCEPT MAP ASSESSOR (CMA) We have designed a prototype computer system for making structured concept map assessment called Concept Map Assessor (CMA). CMA could enable users to construct unstructured concept maps. One could use different shapes, colors, fonts, backgrounds etc. for each node and connection in the concept map. CMA interface works bilingually both in Turkish and English. CMA has two different modes of operation for both constructing a concept map and assessing it. One could transfer the paper-and-pencil concept maps, such as the one in Figure 1, to CMA in the construction mode (Figure 2). This mode is mainly used by the evaluators to prepare the unstructured concept maps for testing students. In the assessment mode, CMA adopt a structured approach in a way that it limits the usage of students concepts and relations to the available concepts and relations in the pre-designed concept map. CMA puts another panel containing names of the concepts and relations in order for user to be aware of the possible choices (See Figure 3). Evaluators may also put extra alternatives in order not to trivialize the assessment. Students may drag and drop the names to appropriate places. For the simplicity, this version of CMA allows only the concepts to be moved and relations are shown in their proper places. Figure 2. A screenshot from CMA in construction mode. Scoring of the students responses in CMA is not integrated to the system yet because of the uncertainty of grading mechanisms of structured concept map assessment on the theoretical grounds. It is proposed that grading mechanisms of unstructured concept map assessment is not directly applicable here. However, the intra-level and extra-level relations of concepts and relations should be taken into the consideration. But, the complexity of the concept map makes the assessment difficult since there might be many main ideas and sub-ideas to be considered. We are still in the process of developing a proper grading mechanism for CMA. CONCLUSION There might always be drawbacks in constructing and assessing concept maps since the relations between concepts might be very complex and non-linear. Furthermore, many sub-ideas might also be related to one another aside from their connections to the main idea. Hence, concept maps should be used cautiously in assessment. CMA provides an environment where evaluators may easily construct concept maps of their domain and use them as an alternative assessment tool at least for a diagnosis purpose at this stage. CMA simplifies the usage of concept maps as a part of assessment. It is proposed that CMA has the potential to be used as a part of teaching and learning process provided that a proper grading mechanism is developed. REFERENCES Anderson, R. (1988). Why talk about different ways to grade? The shift from traditional assessment to alternative assessment. New Directions for Teaching and Learning, 74, 5-16. Cañas, A. J., Ford, K.M., Coffey, J. C. (1994). Concept Maps as a Hypermedia Navigational Tool. Paper presented at the Seventh Florida Artificial Intelligence Research Symposium, Pensacola, FL. Cmap tools (2004). Retrieved from http://cmap.ihmc.us/ on September,20, 2004. Concept Mapping Homepage (2004). Retrieved from http://users.edte.utwente.nl/lanzing/cm_home.htm on September, 10, 2004. Copyright The Turkish Online Journal of Educational Technology 2002 5
Ford, K. M., Cañas, A. J., & Coffey, J. C. (1993) Participatory Explanation. Paper presented at the Proceedings of FLAIRS 93: Sixth Florida Artificial Intelligence Research Symposium, Ft. Lauderdale, FL(pp. 111-115). Ginn, S. B. (1996). Silver Burdett Ginn Science Discovery Works Assessment Guide, Grade 4, NJ.: Silver Burdett Ginn Inc. Hamacmek, D.E. (1986). Humanistic Psychology, In J.A. Glover& R.R. Ronning (Eds), Historical of Educational Psychology, New York: Plenium Press. Lanier, P. (1997) Assesment in the Service of Instruction. Paper presented at the Annual meeting of the National of Supervisorsof Mathematics, St.Paul, MN. Novak, J. D., & Gowin, R. (1984). Learning how to learn (3 rd Edition). New York: Cambridge University Press. Novak, J.D. (1998). Learning, creating and using knowledge: Concept maps as facilitative tools in schools and corporations. Mahwah, NJ: Lawrence Erlbaum Associates. Mwakapenda, W & Adler, J. (2002). Do I still remember? : Using concept mapping to explore student understanding of key concept in secondary mathematics. In C. Malcolm& C. Lubisi (Eds), Proceedings of the 10. Annual Conference of the Southern African Association for Research in Mathematics Science and Techology Education (Part II, pp.60-67). Durban: University of Natal. Park, K.& Travers, K (1996). A Comparative Study of a Computer-Based a Standard College First- Year Course. Dubinsky, E., Schonfeld,A., & Kaput,J. (Eds), Research In Collegure Mathematics Education. II., Providence, RI: American Mathematical Society (155-175). Roth, W.R. & Roychoudhury, A. (1992). The social construction of scientific concepts or the concept map as conscription device and tool for social thinking in high school science. Science Education, 76(5), 531-557 Skemp, R. (1987). Teachology of Learning Mathematics Expanded American Edition. Hillsdale, NJ: Lawrance & Associates, Publishers. Copyright The Turkish Online Journal of Educational Technology 2002 6
A COMPUTER BASED PROBLEM SOLVING ENVIRONMENT IN CHEMISTRY İbrahim BILGIN, Erol KARAKIRIK Abant Izzet Baysal University, Faculty of Education ABSTRACT The purpose of this study was to introduce the Mole Solver, a computer based system that facilitates monitors and improves the students' problems solving skills on mole concept. The system has three distinct modes that: i) finds step by step solutions to the word problems on the mole concept ii) enable students to solve word problems on their own by using appropriate problem solving strategies iii) makes students aware of four step problem solving process. INTRODUCTION One of the goals of science education is to develop the learners' ability to acquire knowledge in specific subjects and to improve their problem solving skills. Problem solving requires overcoming all the impediments in reaching a goal. Many researchers showed that problem solving is one of the most important goals and a desired outcome of learning chemistry (Herron, 1996; Gabel and Bunce, 1994). Reid and Yang (2002) states that inappropriate chemical knowledge prevents students problem solving ability in chemistry and students becomes unsuccessful if chemistry instruction does not provide them with an adequate set of rules to follow or do not help them to understand chemical knowledge during the learning process. Hence, it is essential to help students to understand the pre-requisite knowledge and skills of problem solving and avoid them just simply apply memorized skills in rote fashion. Problem solving has been defined in variety of ways. Dewey (1938) stated that a problem is anything that gives rise to doubt and uncertainty. According to Wheatley (1984) problem solving is defined broadly as what one does when one does not know what to do. Problem solving requires the logical and creative thinking (Bybee and Sund, 1990). Gagne (1977) defined the problem solving as a thinking process by which the learner discovers a combination of previously learned rules that he can apply to solve a novel problem. Pizzini (1989) defined the problem solving as a method of learning as well as an outcome of learning. Many researchers indicates that the use of problem solving instructional models and techniques to teach science influences the problem solving skill of students. Problem solving skills are promoted by providing an rich environment in potential for exploration and by encouraging students to reflect on their actions (Hass and Parkay, 1993). Polya (1957) systematized the efficient PS process as four stages: understanding the problem, devising a plan, carrying out the plan and looking back. Problem solving skills are specifically important in the quantitative problems of chemistry. Nakhleh (1993) and Silberman (1981) points out that high school and freshmen chemistry students find it difficult to solve quantitative chemistry problems. Many studies indicates the importance of mole concept because of its direct link to other quantitative problems in chemistry (Niaz, 1995; Staver and Lumpe, 1995). It has also been suggested that understanding of mole concept is fundamental to students understanding of other chemical topics such as molecular mass, molar concentration, molar volume, ph and chemical equilibrium (Voska and Heikkinen, 2000). Students have difficulties in understanding the mole concept in chemistry and in applying their knowledge during problem solving because of its abstract nature. These difficulties might stem from the learner's psychological development, mathematical anxiety, visual abilities and the instructional methods employed (Reid and Yang, 2002). Hence, it is necessary to develop new learning environments incorporating the instructional strategies to enhance the learning of abstract science concepts in order to develop learner's problem solving skills. In this study, The Mole Solver, a computer based problem solving system, will be introduced. THE MOLE SOLVER The Mole Solver(MS) is a computer based problem solving environment that facilitates, monitors and improves the students' problems solving skills on mole concept. MS was designed specifically for encouraging students to participate actively into the problem solving process and facilitate their problem solving skills in chemistry. It has a built-in expert system that could analyze the word problems on the mole concept. MS analyze the word problem and converts the problem definition into givens and unknowns. The problem analysis phase of MS is language dependent and could analyze only Turkish text for the time being since the system was primarily developed for Turkish audience. MS searches for some predefined keywords in the written text and it tries to convert them into (amount, type, unit) pairs. MS recognizes mole, gram, litre, avagadro number, molecule number as the input unit. The amount should be written as numbers. MS could recognize floating point numbers Copyright The Turkish Online Journal of Educational Technology 2002 7
such as 5.72 as well as avagadro numbers such as 3.21*10^21. One could enter any of the elements in the periodic table as the type. MS also supports compounds. MS could also distinguish the special properties of the elements from its knowledge base such as whether it is a gas or not. However, it may sometimes require to enter special words, such as gas, to define the problem correctly. MS then groups the founded pairs into givens and unknowns by its predefined rules. There is not any limit to the number of pairs to be defined in the problem. However, two or there pairs is generally enough to define most of the mole problems. Table 1 summarizes some pairs found for a few examples of Turkish word problems. Table 1: Some Problem types MS could analyze properly Problem Definition Givens Unknowns Text Amount Unit Type Amount Unit Type 14 gram Fe atomu kaç moldür 14 gr Fe? mole Fe 0.04 mol Ca atomu kaç gramdır 0.04 mole Ca? gram Ca 56 gram Cl kaç mol NaCl bileşiğinde vardır? 56 gr Cl? mole NaCl NŞA 6.72 litre CH4 gazı kaç moldür? 6.72 lt CH4? mol CH4 0.3 mol O2 gazının yapısında kaç tane O atomu vardır? 0.3 mole O2? Avagadro no O MS has also facilities to enter the mole problems directly as givens and unknowns in a language independently manner and gives opportunity to the user to correct the mistakes resulting from an improper analysis of the problem by the system. Data Input Window of Mole Solver includes three distinct places to enter amount, unit and type respectively (See Figure 1). The unknowns could be defined by entering a question mark in the amount. This window also has facilities to delete or change the properties of pairs and to check and analyze the problem definition itself. Figure 1: Data Input Window of Mole Solver MS solves the entered problems with the help of its strategies. Table 2 summarizes the implemented strategies for the system. Table 2: Problem Solving Strategies implemented in Mole Solver Strategy Names Transfer from Gram to Mole Find part from a Whole Transfer from Mole to Gram Find Whole from Part Transfer from Mole to Litre Transfer From Avagadro No to Mole Transfer From Litre to Mole Transfer from Molecule No to Mole Transfer from Mole to Atom No Transfer From Molecule No to Avagadro No Transfer from Mole to Molecule No Transfer from Avagadro No to Molecule No Apart from the problem definition, MS works bilingually both in Turkish and English and could output its results in English as well since it produces its results generically from a pre-specified text. Table 3 gives examples of Turkish and English text to convert the result of the application of a strategy by the problem solving engine of Copyright The Turkish Online Journal of Educational Technology 2002 8
MS although there might be sometimes language dependent details. The %s parameters in the explanations are replaced by the appropriate values found by the system while producing the output. Table 3: Explanatory texts for the transfer from Gram to Mole Strategy Language Explanation English Firstly Let us compute how many grams a mole of %s is:\n A mole of %s contains %s elements.\n Its value is:%s = %s gram.\n If a mole of %s is %s gram, then %s Mole of %s is x gram.\n Then we find: x= %s * %s and x=%s\n Hence %s Mole of %s is %s Gram.\n Turkish Öncelikle 1 Mol %s ifadesinin kaç gram olduğunu hesaplayalım:\n 1 Mol %s ifadesi içinde %s elementlerini barındırır.\n Bu ifadenin değeri toplam:%s = %s gramdır.\n 1 Mol %s %s gram ise,%s Mol %s x gramdır.\n x= %s * %s ise x=%s\n %s Mol %s %s Gramdır.\n There are three different modes of operation for MS: auto solving mode, normal mode, and Polya problem solving mode. Auto Solving Mode: In this mode, MS automatically converts the entered text into givens and unknowns and finds the solution itself if it could be deduced from the givens with the help of available strategies (See Figure 2). It applies all the applicable strategies exhaustively and then deletes the unnecessary strategies while producing the final output. Figure 2: Auto Solve Mode of Mole Solver Normal Mode: In this mode, users are required to enter themselves the problem by data input window. The users could ask the system to produce givens and unknowns or may modify the givens and unknowns pairs themselves. MS does not produce the solution automatically and requires users to select appropriate strategies to apply from the strategies menu (See Figure 3). One needs to select a given to apply a strategy and MS activates or deactivates the strategies with respect to the selected given. One could also apply strategies not directly related to the solution. These unnecessary strategies then could be removed by a related menu item remove unnecessary solution steps. Copyright The Turkish Online Journal of Educational Technology 2002 9
Figure 3: Normal Mode of Mole Solver Polya Problem Solving Mode: In this mode, users are required to follow the four steps of Polya s problem solving method. Users are forced to complete each step: the step of understanding problem and entering data, the step of preparing a solution plan, the step of executing the plan and the step of revision of the solution. In the first step, they are required to enter givens and unknowns. In the second step, they are required to prepare a solution plan with the help of the strategies. In this step, the results of the execution of the strategies are not shown completely and numbers are replaced by letters to focus on the plan rather than the actual result (See Figure 4). In the third step, MS executes the selected strategy automatically for the user. In the fourth step, MS provides feedback to the user whether the solution is found or not. Figure 4: Preparing a Plan in the Polya Problem Solving Mode of Mole Solver CONCLUSION Mole Solver provides a flexible problem solving environment where users could develop their problem solving skills on mole concept. The problems on mole concept are usually algorithmic and MS gives user opportunities to try their strategies in its various modes. MS could analyze the problem for the user and may help them to understand problem definition and show the possible solution in the early stages of teaching of the subject. REFERENCES Bybee, R.W and Sund, R.B. (1990). Piaget for Educators. Second Edition. Waveland Press, Inc. Dewey, J. (1938). Experience and Education. New York, NY: Collier. Gabel, D.L and Bunce, D.M. (1994). Research on problem solving: chemistry. In D. L. Gabel (ed), Handbook on Science Teaching and Learning: A Project of the National Science Teacher Association (New York: Macmillan). Copyright The Turkish Online Journal of Educational Technology 2002 10
Gagne, R.M. (1977). The Conditions of Learning. 3 rd Edition. New York, Holt, Rinehart and Winston. Hass, G and Parkay, F.W. (1993). Curriculum Planning: A new Approach. Ally and Bacon A Division of Simon & Schuster, Inc. Massachusetts. Herron, J.D. (1996). The Chemistry Classroom: Formulas for Successful Teaching. American Chemical Society, Washington, DC. Nakhleh, M.B. (1993). Are our students conceptual thinkers or algorithmic problem solvers? Identifying conceptual students in general chemistry. Journal of Chemical Education, 70, 52-55. Niaz, M. (1995). Cognitive conflict as a teaching strategy in solving chemistry problems: A dialecticconstructivist perspective. Journal of Research in Science Teaching, 32, 959-970. Pizzini, E.L, Shepardson, D.P and Abell, S.K (1989). A Rationale for and the development of a Problem Solving Model of Instruction in Science Education. Science Education, 73, 523-534. Polya, G. (1957). How to solve it. Garden City, NY: Doubleday and Co., Inc Reid, N and Yang, M.J. ( 2002). The solving of problems in chemistry: the more open-ended problems. Research in Science & Technological Education, 20, 83-98. Silberman, R.G. (1981). Problems with chemistry problems: student perception and suggestions. Journal of Chemical Education, 58, 1036. Staver, J.R and Lumpe, A.T. (1993). A content analysis of the presentation of mole concept in chemistry textbook. Journal of Research in Science Teaching, 30, 321-337. Voska, K.W and Heikkinen, H.W. (2000). Identification and analysis of student conceptions used to solve chemical equilibrium problems. Journal of Research in Science Teaching, 37, 160-176. Wheatley, G.H. (1984). MEPS Technical Report, Mathematics and Science Centre, Purdue University ( cited from Zoller, U. (1987) The fostering of question-asking capability. Journal of Chemical Education, 64, 510-512. Copyright The Turkish Online Journal of Educational Technology 2002 11
A METADATA MODEL FOR E-LEARNING COORDINATION THROUGH SEMANTIC WEB LANGUAGES Atilla ELCI, Assoc. Prof. Dr. Semantic Web Workgroup, Internet Technologies Research Center, Dept. of Computer Engineering, Eastern Mediterranean University, G. Magosa, TRNC. Atilla.Elci@EMU.edu.tr, Tlph. +90-532-351-4425, +90-392-630-2843 ABSTRACT This paper reports on a study aiming to develop a metadata model for e-learning coordination based on semantic web languages. A survey of e-learning modes are done initially in order to identify content such as phases, activities, data schema, rules and relations, etc. relevant for a coordination model. In this respect, the study looks into the mechanism of e-learning environment and the question of how e-learning can be classified in terms of activity coordination. A metadata model for coordination of e-learning is being sought which may be expressed using semantic web languages such as OWL + RDF. This is part of a project involving studies on several fronts regarding the application of semantic web initiative into e-learning; i.e. design and development of markup and annotation tools, relevant ontologies, intelligent agents, etc. The objective is eventually to build capability to semantically integrate and selectively retrieve e-content in implementing e-learning environments. KEYWORDS Semantic web, OWL, RDF, XML, markup, ontology, knowledge grid, semantic grid, information retrieval, intelligent agents, interfaces, markup tools, modeling e-learning, LMS, LTSC, LTSA, LOM, ADL, SCO, SCORM. INTRODUCTION There are numerous names for open, flexible and distributed learning activities, including E-Learning, Web-Based Learning (WBL), Web-Based Instruction (WBI), Web-Based Training (WBT), Internet- Based Training (IBT), Distributed Learning (DL), Advanced Distributed Learning (ADL), Distance Education (DE), Distance Learning (DL), Online Learning (OL), Mobile Learning (or m-learning) or Nomadic Learning, Remote Learning, Off-site Learning, a-learning (anytime, anyplace, anywhere learning), and of late, terms like Instructional Technology, Learning Technologies, and Learning Management System, etc. Precise definitions of such terms can be found in the literature (see, for example: [CDLP], [Moore-1996], [LTSC-1996], [Tsai- Machado] and [ACM-eLearn]). While we concede to that there is considerable difference among some of these in purpose, application, parties involved, tools used, etc., we tend to utter e-learning as an all-encompassing generic term. This is quite in line with our predisposition in this paper for we wish to consider e-learning in its generic form equally far away from any flavor of it. Of specific interest, IEEE LTSC defines learning technologies as the development, deployment, maintenance, and interoperation of computer implementations of education and training components and systems. Instructional technology may be defined as being the systemic and systematic application of strategies and techniques derived from behavioral, cognitive, and constructivist theories of learning to the solution of instructional problems. This paper reports on a study aiming to eventually develop a metadata model for e-learning coordination based on semantic web languages. We will show that e-learning requires a heavy dose of control and coordination where the findings of this study can be useful. Information technology (IT) has always attracted attention from all quarters of interest; the education/training is no exception. Famous educationist Chris Dede recounts his recent initiative to utilize high tech IT gadgets in training projects in an interview [Morrison-2004]. Whereas we highly sympathize with such utilization of IT gadgetry to individual learner s benefit, our interest lies in the softer side, that is, typically in effecting e-content and rendering it accessible through intelligent software agents. Many e-learning models exist, some heuristic, others well-grounded on specific instructional design approaches. We will mention some here and our point of interest will be on control and coordination (C&C) aspects. Salmon (2002) argues that the role of online teacher is evolving from that of conveying known information to one of facilitating exploration and generating new knowledge. Primarily this shift in the part played, but also the complexity of the technology employed, necessitates a highly elevated designation such as e-moderator. It is clear that the elevated role of e-moderator is mostly due to C&C it exercises. Copyright The Turkish Online Journal of Educational Technology 2002 12
The well-known creativity researcher Mihaly Csikszentmihalyi coined the term flow to mean a creative activity process that is both enjoyable and challenging that engulfs one to the extent of loosing track of time while doing it [Csikszentmihalyi-1990]. Likening the instructional design process to the flow concept and striving to create a flow-like environment for instructional design, Ceraulo (2003a) identifies seven characteristics for carrying it out highly effectively: 1. Focus goals 2. Eliminate distractions 3. Match student skills and course 4. Create a supportive environment level 5. Create order through rules 6. Let students express themselves, and 7. Provide timely and consistent feedback. According to Ceraulo (2003b), similar characteristics apply in the case of online teaching. Of those, with respect to C&C, we would be reasonably interested in 3 rd - 7 th activities. Khan (2003) introduces a Framework for e-learning with eight dimensions: 1. Institution (admin, academic, student services), 2. Pedagogy (teaching and learning), 3. Technology (infrastructure), 4. Interface design, 5. Evaluation (assessment and evaluation), 6. Management (learning environment), 7. Resource support, and 8. Ethics. Figure 1 depicts these pictorially. Furthermore, each dimension has several indicative issues of focus. The purpose of the framework is to assist during steps of the e-learning design process. The framework with its concomitant checklist can be used to ensure that all relevant factors are taken into consideration during the design and development of e-learning. It is clearly a welcome contribution, as the scope and extent of e-learning expands rapidly, consequently projects will require complex team efforts. Existence of a mature framework and an extensive checklists stemming from it, help greatly to control and coordinate activities of parties involved. The complete list of dimensions and sub-dimensions may be accessed at URL http://www.bookstoread.com/framework/scroller.htm. The above framework presents a model of dimensions, that is to say, interest areas. The E-Learning P3 Model proposes a model embodying a process standpoint [Khan-2004]. Considering the people process product continuum in e-learning, it contributes greatly towards this study. Table 1 identifies 35 roles and their responsibility. It is judged that almost all of the roles involve C&C. That alone would justify our concern with C&C aspects in e-learning systems and solutions. Similarly McPherson and Nunes (2002) contains a few process oriented models. Importance of coordination aspects in e-learning was substantiated by another study. Aiming at evolving a new instructional design model, Ling and partners set to determine most relevant scaffoldings in Web-based learning [Ling-2001]. They found that the support, learner s engagement, learner s participation, multimedia integration and learner interaction were the most influential in success. Clearly these are all related to coordination. Copyright The Turkish Online Journal of Educational Technology 2002 13
A consortium-led research program is working on a Web-based heuristic advisory system for instructional designers [Niegemann-2002]. The system will provide design options, connected costs and possible consequences for every level of design decisions. It will be more like a decision support system for instruction designers. To be able to construct such a system, one requires a good understanding of main categories of functional elements used in ID models and the main levels of design decisions. That will lead to a set of important control and cooperation relationships. On the other hand, the Learning Federation hints on the future shape of education [TLF-2001]. By the year 2020, the next generation learning systems will draw from a robust array of software tools. Software will provide intelligent and context sensitive support on all aspects of learning and teaching. This can only be possible through e-learning integrating with a semantic Web base. More on this issue later. Riddy and Fill list the existence of Integrated Environments for elearning among the prime critical success factors (CSF) [Riddy-Fill-2002]. Referred to are several examples of substantial initiatives that are developing and future-proofing educational environments, and provide pointers to some technological necessities for successful elearning. These are the Open Knowledge Initiative s (OKI s) software architecture, MIT s Open CourseWare (OCW) Stella and UK euniversities Worldwide s next generation elearning system [PWC-2000] [Collier-2002]. These have been early projects each with its particular empirical foundation and resolution of practical matters. Findings of them have enriched important model studies by prominent research organizations in recent years. The major bodies involved have been the IEEE Learning Technology Standards Committee (LTSC), Aviation Industry CBT Committee (AICC), Instructional Management Project (IMS), EU ARIADNE project, Advanced Distributed Learning (ADL) initiative of the US Department of Defense- SCORM (Shareable Courseware Object Reference Model) developments, and Microsoft Learning Resource Interchange (LRI) specification. The work of these bodies has been far reaching. The LTSC has been developing definitions of all aspects of learning technology [LTSC]. It introduced the broad definition of learning objects (LOs) concept together with related models. Likewise it has been producing relevant standards with much acceptance by others. For example, its Learning Technology System Architecture (LTSA) [LTSA-2001] standard was adopted by the ADL as bases for further improvement of the Content Aggregation Model (CAM) of the SCORM [SCORM-2003]. One year into subsequent development it was realized that there's something missing in SCORM: the process of creating complex behaviors, such as remediation branching, wasn't supported well (or at all) in the current CAM specifications. So ADL had to build a Navigation and Sequencing part in cooperation with IMS and grafted it to SCORM. This outcome is exactly due to lacking of what we have been pointing out as a must CSF, that is, C&C is required for purposes of environment integration. Sequencing of learning objects (LO s) without embedding sequence indication into them will allow shareable free standing LOs. Control over prescribed advancement of learner through courseware is a basic delivery requirement. Backtracking (for remedial purpose), reiterating (for coverage of further detail), synchronizing several learners at stages (say, before testing), temporary digression (say for deficiency training or info look up) with or without freezing the current state, etc. are also required. The origin of this lacking is actually stemming from LTSA. Figure 2 displays the hierarchic layers of LTSA where Layer 1 is at the top and Layer 5 at the bottom. There exists an interface between any two layers performing filtration function between abstraction from the layer above to implementation at the lower layer. A lot of C&C issues need be inserted at the interfaces, with the most of the rest going into the layer logic. What is not suitable or feasible for inclusion is left out. Instead, LTSA should have a dedicated C&C layer separate from the others. It is conjectured that, due to lasting relations with each layer, the C&C layer should be positioned perpendicular to others that is, in full contact with all the interfaces and layers at all times. This we depict in Figure 2. Copyright The Turkish Online Journal of Educational Technology 2002 14
Figure 2. The IEEE LTSA layers [LTSA-2001]. The drawing on the right is not part of LTSA but being proposed by this paper. In our proposal, each LTSA layer corresponds with the C&C Layer for all control and coordination issues. LTSA layers become processing plateaus for their designated specific functions. Layer interfaces similarly implement pass-through function calls to down-up layers where filtering is based on that specified by the C&C Layer. Consequently, LTSA becomes a generic architecture, that is, not involving inclinations towards any LMS scheme or kind of e-learning approach (ref. definitions in the introduction above). At this juncture, there is an opportunity not to be missed: incorporation of semantic Web based approach (SWA) to LO design and development. This process may start with infusion of SWA into the design of the C&C Layer and into LTSA for which we will require an extensive metadata set to be gathered on C&C issues. The standardization of LOs holds out the promise of re-usable learning materials. Increased use of metadata and XML to incorporate tags or labels within e-learning content will provide new structure to documents that software systems can interpret. Encoding the tags in a particular way, using the Resource Description Framework (RDF) allows the building a network of related information on the go. Combining these with ontology, to further define the relationships between objects, will lead to the Semantic e-learning (after [Berners-Lee et al-2001]). The real power of the Semantic Web will be realized by agents, software programs that can search the Web to find specified information. This could herald a new era of collaborative developments, enhancing tutors abilities to work within e-learning environments and providing learners with what they want, when they want it. This would be quite in line with findings of a recent think-tank workshop organized by Computing Research Association on determining the Grand Research Challenges in Information System. One of the five grand challenges is Providing a teacher for every learner, that is, tutoring each individual in a tailored, learnercentered format to enable people to more fully realize their potential [CRA-2002]. CONCLUSION There is need to involve semantic Web approach at all stages of e-learning [EU-IST-2004]. The semantic Web makes web resources understandable to software agents. By incorporating the meaning and context (semantics) of information, it brings structure to the web through capability to interpret its constituent resource. The concept of web services, where online transactional services are loosely coupled through common directories and exchange protocols, has also gained solid ground. Eventually, e-content will be rendered easier and friendlier to use and a better tool to serve all information needs. E-learning activities doubtless will draw benefit from being able to generate semantic metadata, to structure, filter, retrieve and maintain it in semantically so as to turn data into shareable knowledge. Thus, in the long-term, e-learning systems will use semantic Web-based knowledge systems as key parts of everyday learning cycles. REFERENCES - [EU-IST-2004] Turning Information Systems into Knowledge Resources. In Europe s Information Society Thematic Portal- Semantic Web; accessed on October 2004. http://europa.eu.int/information_society/policy/nextweb/semantic/index_en.htm. - [CDLP] California Distance Learning Project: What is Distance Learning? http://www.cdlponline.org/index.cfm?fuseaction=whatis; accessed on October 9, 2004. - [Moore-1996] Distance Education: A Systems View: What is Distance Education? http://www.cde.psu.edu/de/what_is_de.html; accessed on October 9, 2004. - [LTSC-1996] Learning Technologies, http://www.informatik.uni- Copyright The Turkish Online Journal of Educational Technology 2002 15
bremen.de/uniform/gdpa/def/def_l/learning_tech.htm; accessed on October 9, 2004. - [ACM-eLearn] ACM elearn Magazine: http://www.elearnmag.org/index.cfm; accessed on September 27, 2004. - [Salmon-2002] Salmon, Gilly: Masters or slaves to the technology? The Role of the e-moderator in e-learning. ACM elearn Magazine, 2002; visited October 2004. http://www.elearnmag.org/subpage/sub_page.cfm?section=4&list_item=1&page=1. - [TLF-2001] The Learning Federation: Next generation learning systems and the role of teachers. In 2020 visions: Transforming education and training through advanced technologies, pp: 15-19. Washington, DC: Technology Administration, U.S. Department of Commerce. http://www.ta.doc.gov/reports/techpolicy/2020visions.pdf (accessed October 2004). - [Csikszentmihalyi-1990] Csikszentmihalyi, Mihaly: The Psychology of Optimal Experience, Harper Collins, 1990. - [Ceraulo-2003a] Ceraulo, Sandra C: Instructional design for flow in online learning, in ACM elearn Magazine, 2003; visited September 2004. http://www.elearnmag.org/subpage/sub_page.cfm?section=4&list_item=10&page=1. - [Ceraulo-2003b] Ceraulo, Sandra C: Instructional design for flow in online teaching, in ACM elearn Magazine, 2003; visited September 2004. http://www.elearnmag.org/subpage/sub_page.cfm?section=4&list_item=14&page=1. - [Khan-2003] Khan, B. H.: A Framework for Open, Flexible and Distributed E-Learning, in ACM elearn Magazine, 2003; visited October 2004. http://www.elearnmag.org/subpage/sub_page.cfm?section=3&list_item=12&page=1. - [Khan-2004] Khan, B. H.: People, process and product continuum in e-learning: The e-learning P3 model. Educational Technology. Vol. 44, No. 5, pp. 33-40. (2004, September-October). See: http://www.bookstoread.com/ for a copy. - [Ling-2001] Ling, Siew-Woei, Khong, C-W, and Lee, C-S: An evolving instructional design model for designing Web-based courses. DOI: 0-7695-1013-2/01, IEEE, 2001. - [Morrison-2004] Morrison, J. and Dede, C. 2004. The Future of Learning Technologies: An Interview with Chris Dede. Innovate, October/November 2004. http://www.innovateonline.info/index.php?view=article&id=1 (accessed October 10, 2004). - [Niegemann-2002] Niegemann, Helmut M.: Developing a Web-based heuristic advisory system for instructional designers, in Proceedings of the International Conference on Computers in Education (ICCE 02), IEEE, 2002. - [PWC-2000] PricewaterhouseCoopers report: e-university Project business model, 10 October 2000. http://www.hefce.ac.uk/pubs/hefce/2000/00_44.htm); accessed on October 2004. - [Tsai-Machado] Susanna Tsai and Paulo Machado: E-learning, Online Learning, Web-based Learning, or Distance Learning: Unveiling the Ambiguity in Current Terminology. http://www.elearnmag.org/subpage/sub_page.cfm?section=3&list_item=6&page=1; accessed on September 27, 2004. - [ICCE-2002] Maggie McPherson, Lyn Henderson, and Kinshuk (editors): Proceedings of the Workshop on The Changing Face of HE in the 21st Century: Critical Success Factors (CSFs) for Implementing elearning; held in conjunction with International Conference on Computers in Education (ICCE2002), 3-6 December 2002, Auckland, New Zealand. ISBN 0-473-09631-5. http://icce2002.massey.ac.nz/; accessed on October 9, 2004. - [Riddy-Fill-2002] Paul Riddy and Karen Fill: Technological CSFs for elearning implementation. pp: 15-19 in [ICCE-2002]; accessed October 2004. - [McPherson-Nunes-2002] Maggie McPherson and Miguel Nunes: A Framework to support elearning management. pp: 1-7 in [ICCE-2002] ; accessed October 2004. - [Collier-2002] G. Collier: e-learning Application Infrastructure. SUN Microsystems White Paper.2002. Available online at: http://www.sun.com/products-n-solutions/edu/whitepapers/ pdf/elearning_application_infrastructure_wp.pdf ; accessed on October 5, 2004. - [ADL] ADL: Advanced Distributed Learning Initiative of the US Government, Department of Defense. http://www.rhassociates.com/adl.htm and http://www.adlnet.org; accessed on October 2004. - [SCORM-2003] SCORM: Sharable Courseware Object Reference Model Available online at: http://www.rhassociates.com/scorm.htm; accessed on October 2004. - [LTSC] Thee IEEE LTSC home page is http://ltsc.ieee.org/; accessed on October 9, 2004. - [LTSA-2001] IEEE Learning Technology System Architecture (LTSA). Home page: http://www.informatik.uni-bremen.de/uniform/gdpa/gdpa06.htm. Draft 9: http://edutool.com/ltsa/09/ieee_1484_01_d09_ltsa.pdf; accessed on October 8, 2004. - [Berners-Lee et al-2001] Berners-Lee, T., Hendler, J. and Lassila, O.: The Semantic Web. Scientific American, May 2001; accessed on September 15, 2004. Copyright The Turkish Online Journal of Educational Technology 2002 16
http://www.scientificamerican.com/article.cfm?articleid=00048144-10d2-1c70-84a9809ec588ef21&catid=2. - [CRA-2002] Grand Research Challenges in Information Systems, final report of CRA Conference on "Grand Research Challenges" in Computer Science and Engineering, June 23-26, 2002, Airlie House, Warrenton, Virginia, USA by Computing Research Association. http://www.cra.org/reports/gc.systems.pdf; accessed September 23, 2004. Copyright The Turkish Online Journal of Educational Technology 2002 17
A MODEL FOR INTEGRATING NEW TECHNOLOGIES INTO PRE-SERVICE TEACHER TRAINING PROGRAMS AJMAN UNIVERSITY (A CASE STUDY) Dr. Ali Zuhdi H. Shaqour Educational Technology Dept. College of Education and Basic Sciences Ajman University of Science and Technology Network Email : Zuhdi4@yahoo.com ABSTRACT This study introduces a Technology Integration Model for a learning environment utilizing constructivist learning principles and integrating new technologies namely computers and the Internet into pre-service teacher training programs. The technology integrated programs and learning environments may assist learners to gain experiences using technologies for purposes like constructing new knowledge and working collaboratively as these technologies provide learners with opportunities for learning characterized by flexibility, discovery and reflection as well as knowledge construction. Exposing these teachers to such technologies give them a chance to gain technology related skills and knowledge (S&K) for their future careers like dealing with the Internet and desktop publishing. Implementing of one of constructivist strategies namely collaboration in this environment would be beneficial for both faculty and learners as it shifts the whole teaching/learning process from teacher-centered in which the teacher is information transmitter and the learner is a passive recipient to learner-centered in which she/he becomes the main player and an active participant in the process. Keywords: technology integration model, Internet tools implementation in the learning process, learning with technology, online learning. INTRODUCTION Educational technology is an evolving discipline which is strongly affected by the advancement and development of technology. This discipline was remarkably influenced by thoughts of the members of The Association for Educational Communications and Technology (AECT) which played a vital role in the field since the sixties. This organization provided a definition to the field of instructional technology. Ely (1968), one of its members described educational technology as a branch of educational theory and practice concerned "primarily with the design and use of message which controls the learning process." He also provided a description to Educational Technology as "a field involved in the facilitation of human learning through the systematic identification, development, organization, and utilization of a full range of learning resources, and through the management of these processes (1972). It is agreed among educational technologists i.e. Romiszowski, 1997; Sharon, 1995; Spencer, 1991; Seigel and Davis, 1986, that the development of the tools of instruction was remarkably traced back to the early 1990s, the period of the audiovisual movement. In that time, the concern was according to Spencer (1991), on the effects of devices and procedures as a remedy to the extreme verbalism of traditional methods of teaching. Davis (1986) talked about the three waves of the technology and the related know-how as follows; The first wave was associated with the new technology itself in designing and programming of computers and applications. This is related to the science of computing and programming (teaching about technology). The second wave was associated with the advent of the cheap microcomputer and its use by a much greater number of people. (teaching through computers). The third wave is characterised by the access of all sectors of social and professional activity to computer systems. (teaching with computers). Today, when we say educational technology we are referring largely to a vast array of computer-based technologies such as compact disc-read only memory (CD-ROM), interactive audio, interactive videodisc, local area networks, hypermedia, and telecommunications. The advent of microcomputers in the 1980s and developments in computerized education in the 1990s, concern educationalists today. Questions arose by educationalists like Ellul (1981), Davis (1992), Bowers (1993) and Turkle (1997). These questions were concentrated on the role that technology will play in the educational field. This probed questions like; should we teach about technology, through technology or with technology? Copyright The Turkish Online Journal of Educational Technology 2002 18
Nowadays technologies of communication and delivery systems have changed the way education can be delivered. Satellite television, the Internet, for example, have transformed the means of how education can be conducted while the World Wide Web evolved from developments of computer networking becomes the main source of information and communication. THE PROBLEM First of all it is worth mentioning that according to my experience, teachers are not well trained to use technology in the teaching/learning process during their pre-service study programs. Solving this problem requires the treatment of all involved components of such programs which are student teachers themselves, their faculty and curriculum programs. Dealing with these components and finding solutions to the overall issue in a short paper like this is hard to reach. So, this paper is an effort to partially solve the problem as it only deals with one part of the problem which is infusing technology in the teacher preparation programs. The remarkable effect that rapid technological development has had on our society is evident in virtually every aspect of our daily life. Thus progress in new technologies (including computers and the Internet), has changed the way we live, the way we do business, the way we communicate with each other and the way we teach and learn. This made it important for our educational establishments i.e. colleges and universities to prepare their graduates to use technology effectively in their future careers. Specifically, teachers in these establishments need to be able to use new technologies in the teaching/learning process in order to help their pupils acquire the (S&K) relevant to and presented by these technologies. According to my experience, as a school teacher for eight years and a university lecturer for six years, most educational establishments in the Arab world and especially in the United Arab Emirates are properly equipped with new technologies (computers, digital cameras, printers, scanners, etc.) and Internet connection. In spite of the availability of such infrastructure, the level of teachers (benefit of) being able to access and use them appropriately and skillfully is quite limited. This view is agreed by researchers participated in the first annual conference of Information Technology Special Interest Group (ITSIG) held in March 2003 at Sharjah University in the UAE. These researchers (and I was among them) expressed their concern regarding the lack of Information Communication Technologies (ICT) S&K teacher trainees acquire during their college study. All speakers agreed that schools must prepare students for the technology- rich jobs in the 21st century. This agreement harmonizes other educators i.e. Clifford & Friesen, 2001; Jacobsen, 2001, calls for a shift in teacher education who must routinely encounter the effective infusion of technology in the normal course of their learning at the university and in their practicum placements in schools. So, student teachers need to be technologically literate in order to excel in future jobs and should learn how to integrate technology for effective and efficient teaching/learning process (how to teach with technology). This might enable them to use technology to expand their instructional repertoire, and thus enhance students' learning. Both technology literacy and learning enhancement would be difficult to reach if teachers roles remain as knowledge transmitters and students roles continued to be knowledge absorption in colleges of education. So, their should be a shift in the teaching/learning process and a role change of both teachers and students in these colleges. This study proposes a model that could shift teachers involved in pre-service teacher training programs from the dominant didactic mode i.e. teacher centered teaching to a more student-centered one. The importance of the proposed model of this study lies on offering instructors involved in teacher preparation programs an approach of teaching/learning process that shifts them from the dominant didactic model i.e. teacher centered teaching to a more student-centered one. This model depends heavily on working collaboratively using internet tools i.e. e- mail and e-group discussion as an enhancement and supplement of collaboration occurs in classroom. This learning strategy of the model is elicited from constructivism principles in order to achieve meaningful learning through the construction of new knowledge (Jonassen, et al 1991). So, when implemented, the model could help inexperienced teachers acquire proper related S&K to be implemented in their future careers, as teachers of tomorrow s classrooms. The possibilities and effectiveness of such environment are explained through reviewing related literature and research findings in order to construct an understanding of the impact of these technologies on learning among pre-service teachers educators. Finally, the learning environment in which this model is implemented may open the doors in front of the learners for global education (Mason, 1998; Mills, 1999) through gaining proper ICT S&K which can enable them to communicate with their peers all over the world. This is of great importance for these learners to deal with global perspective on issues related to their specializations. In addition, this environment could overcome some cultural barriers in universities like AUSTN where gender separation is a common practice. 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THE THEORY BEHIND THE PROPOSED MODEL Constructivism as a learning theory, argues that learning is constructed as an active process in which learners construct their new ideas or concepts based on their current or past knowledge in a meaningful learning environment. The key to learning, in a constructivist framework, is for the learner to find multiple ways to link new information to previous experience "learners actively construct and reconstruct knowledge out of their experiences in the world" (Kafai and Resnik, 1996). Such thoughts contradict the practices of most instructors of teacher preparation programs in which the didactic expository teaching is the dominant method where the teacher is the information giver and the learner is a passive recipient. Such method is criticized by many educators especially constructivists (Oldfather, Bonds, and Bray, 1994; Cannella & Reiff,1994; Richardson,1997). In this didactic, memory-oriented transmission method the teacher fills students with deposits of information considered by the teacher to be true knowledge, and the students store these deposits, intact, until needed i.e. exams. According to Richardson (1997), when information is acquired through transmission methods, it is not always well integrated with prior knowledge and is often accessed and articulated only for formal academic occasions such as exams. According to Jonassen (1991), constructivism proposes that learning environments should support multiple perspectives or interpretations of reality, knowledge construction, contextrich and experience-based activities. So constructivism focuses on knowledge construction, not on knowledge reproduction. Jonassen (1994) summarises the differences between constructivist learning environments and traditional instruction as follows: constructivist learning environments are (a) multi-dimensional, and provide multiple representations of reality, thereby avoiding over-simplification; (b) encourage learner construction of knowledge rather than rote memorization; (c) emphasize meaningful, authentic, contextualized tasks that are anchored in real-world or case-based settings; (d) encourage thoughtful reflection; and (e) emphasize collaboration instead of competition. These characteristics of constructivism learning environment requires active participation among learners with the encouragement, guidance and monitoring of their teacher. Many educators report that useable knowledge is best gained in learning environments where learners are provided with authentic context that reflect the way this knowledge will be used in real-life, authentic activities, multiple roles and perspectives, coaching and scaffolding at critical times. They also promote reflection to enable abstractions to be formed, and articulation to encourage tacit knowledge to be made explicit, in addition to supporting collaborative construction of knowledge. According to, for example, Brown, Collins and Duguid, 1989; Carver, et al., 1992; Jonassen, Mayes and McAleese, 1993, Cognition and Technology Group (CTG) at Vanderbilt, 1990, Brooks and Brooks, 1994, the provision of a practical context, combined with authentic tasks and activities, can provide a learning environment that demands higher order thinking and problem-solving to achieve a satisfactory outcome. These educators discussed models of learning in their writings which promote philosophy of constructivism. Examples of such models are; Reception learning model advocated by David Ausubel in 1968 (in Ausubel, Novak and Hanesian, H;1978). This model suggests that it is the job of the teacher to structure learning, to select appropriate materials for students, and to present them in a well-organized fashion. Scaffolding was conceptualized by Vygotsky. According to Vygotsky, higher mental functions such as the ability to focus attention or memory, or to think in terms of symbols is unique to humans and is passed down by teaching. The development of these functions in this model is tied to social context and culture. In Scaffolding, the teacher guides instruction so that students will internalize these higher functions. Then once these functions are acquired, the student will have the tools necessary for self-guided learning. According to the North Central Regional Educational Laboratory (NCREL), authentic instruction, developed by Fred Newmann (1993) consists of; learning situations that are connected with the context of the learners world, and is a model for high-quality instruction. Newmann lists five major components of the teaching process. These components which are included in his article Crafting Authentic Instruction are; higher-order thinking depth of knowledge connectedness to the world beyond the classroom substantive conversation social support for student achievement. The 5E s Learning Cycle developed by Biological Sciences Curriculum (1993), is another model which promotes the philosophy of Constructivism. The 5E s of this model includes; 1) Engage the learner with an event or question, 2) Explore the concept, skill, or behavior with hands-on experiences, 3) Explain the concept, skill, or behavior, 4) Elaborate on the concept, skill, or behavior by applying it to other situations and 5) Evaluate students understanding of the concept. Copyright The Turkish Online Journal of Educational Technology 2002 20